Nor Mohd Haziq Norsahperi
University of Technology Malaysia, Universiti Putra Malaysia
Papers
6
Total Citations
124
H-Index
4
About
Nor Mohd Haziq Norsahperi is a rising researcher at the intersection of control systems, robotics, and artificial intelligence, whose work spans from theoretical advances in nonlinear control to practical applications in agriculture and medicine. His most influential contribution is an improved optimal integral sliding mode control for uncertain robotic manipulators, published in 2020 with 71 citations, which simultaneously reduces tracking error, chattering, and energy consumption—a significant step toward more efficient and reliable industrial robots. He has also made notable strides in autonomous navigation, authoring a comprehensive 2025 review on deep reinforcement learning for mobile robots in dynamic environments (28 citations), and pioneering the use of YOLOv4 for real-time oil palm loose fruit detection (14 citations), enabling autonomous collection in challenging plantation settings. His comparative study of LQR and integral sliding mode control (7 citations) provides valuable design insights for robotic manipulator control. More recently, Norsahperi has ventured into medical robotics, applying convolutional neural networks for real-time liver and gallbladder segmentation during laparoscopic surgery (3 citations). His work demonstrates a rare ability to bridge rigorous control theory with cutting-edge AI, yielding practical solutions across diverse domains.
Research Focus
Key Achievements
Top Papers
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